Estimating satellite-based precipitation at high latitudes (>60°) currently presents a major challenge in computing global rainfall products. The current generation of satellites used for precipitation estimation rely on either microwave or infrared observations, both of which cannot differentiate between cold or icy surface and frozen precipitation. The Global Precipitation Climatology Project (GPCP) Version 2 (V2) monthly and One-Degree Daily (1DD) overcome this limitation through the use of TIROS Operational Vertical Sounder (TOVS) sounding data, with a transition to the Aqua Atmospheric Infrared Sounder (AIRS) in April 2005. The TOVS estimation technique infers precipitation from clouds using a regression relationship between coincident rain gauge measurements and TOVS-based parameters, including cloud-top pressure, fractional cloud cover, and relative humidity. As part of the GPCP processing, these TOVS precipitation estimates are then scaled to match the fractional coverage of the high-quality DMSP Special Sensor Microwave Imager (SSMI) estimates at the mid latitude regions. The TOVS data is adjusted to the large-scale bias of the available rain gauge data at 70° and the large-scale bias of the SSMI estimates at mid latitudes. Because long-term, expansive ground-based precipitation estimates covering the high-latitude regions are not uniformly available, validating the performance of the GPCP estimates at the higher latitudes has proved difficult. Previous work using the BALTEX basin rain gauges is encouraging. The daily time series of the 1DD and the total BALTEX gauge precipitation data for the year 1997 showed reasonable agreement with rain amounts exhibiting good correlation. This study assesses the currently available suite of high-latitude, ground-based precipitation estimates for further validating the GPCP monthly and daily products. Candidate data sets include the Helsinki Testbed and Serreze basin rain gauge data. Large-scale statistics such as bias, RMS, and correlation are examined. The goal is to quantify the nature of the differences at the high latitudes to further understand the errors associated with the satellite-based GPCP estimates, and allow for bias correction in the next generation GPCP Version 3 precipitation estimates.